Background and Purpose
This assessment tool helps designers, educators, and organisations evaluate how AI is likely to transform specific design tasks over the coming years. It draws on established design theory to provide a comprehensive inventory of designer functions and tasks across the Double Diamond framework.
The key question is not whether AI will fully replace designers, but whether AI enables significant cognitive or skill offload. Can a highly skilled expert be replaced by a less experienced person augmented with AI tools? Even partial automation can fundamentally reshape professional practice, career pathways, and educational requirements.
The tool recognises that impact doesn't require complete AI handoff. A task may be substantially transformed when AI handles the cognitively demanding portions, reduces the expertise threshold, or accelerates execution—even if human oversight remains necessary.
Theoretical Foundations
The framework integrates multiple perspectives on design practice:
Practical Application
The Double Diamond (Design Council) provides the organising structure: Discover and Define phases address problem understanding, while Develop and Deliver phases address solution creation. Within each phase, designer functions group related tasks.
The framework applies across physical product design, service design, and interaction design, recognising that methods flex to context while core cognitive processes remain consistent.
A note on prediction horizons: Forecasting technological change beyond 5 years is highly speculative. The timescales in this tool should be understood as rough indicators rather than precise predictions. The "Long-term" and "Distant/Never" categories acknowledge fundamental uncertainty about whether and when certain capabilities might emerge. Use these assessments to prompt discussion rather than as definitive forecasts.
How to Use This Tool
Navigate to each phase tab and rate individual tasks according to when you believe AI will significantly impact how that task is performed. Consider not just full automation but meaningful skill offload—the point at which the expertise required to perform the task competently is substantially reduced by AI assistance.
The Summary tab aggregates your ratings to highlight which functions and phases face the most imminent transformation.
AI Exposure Timeline Scale
Rate each task by when AI is likely to enable significant skill offload—the point at which the expertise threshold for competent performance is meaningfully reduced. This may occur through automation, augmentation, or AI-assisted workflows that reduce the need for deep specialist knowledge.
Now
AI is already substantially transforming this task. Tools exist and are in active use by practitioners. A less experienced person with AI can approach the output quality of an unaided expert.
Imminent — within 12 months
AI capabilities are emerging rapidly. Significant skill offload expected within the next year based on current trajectories and announced developments.
Near-term — 1 to 3 years
AI will likely impact this task as technology matures and integrates into professional workflows. Clear research directions suggest feasibility.
Mid-term — 3 to 5 years
AI may impact this task, but significant technical or practical barriers remain. Transformation possible but not certain within this window.
Long-term — 5 to 10 years
Fundamental challenges make near-term transformation unlikely. May require breakthroughs in AI capabilities not yet demonstrated. High uncertainty.
Distant / Never
This task may inherently require human presence, judgment, or relational qualities that cannot be replicated by AI—or transformation is beyond any reasonable prediction horizon. Use for tasks where expert human involvement seems irreducibly essential.
Assessment Summary
Overview of AI exposure ratings across all designer functions and tasks. Higher averages indicate tasks likely to face earlier AI-driven skill offload.